Long-haul trucks travelling through a European motorway interchange

Logistics & Transport

Business Intelligence Consulting for Logistics & Transport

Unify your supply chain data, optimise routes, and build real-time visibility across every logistics operation.

The challenge

The Data Problem in Logistics

Logistics data analytics is hard. Fragmented systems, latency, and volume create blind spots that cost money every hour they go unresolved.

Disconnected Systems

TMS, WMS, ERP, telematics, and carrier portals all speak different languages. Data lives in silos, reconciliation is manual, and by the time a report is ready the window to act has already closed.

Reactive Operations

Teams spend hours chasing yesterday's data instead of preventing tomorrow's delays. Without real-time visibility, exception management becomes firefighting and SLA penalties accumulate silently.

Rising Costs, Thin Margins

Fuel, driver hours, and SLA penalties erode margins when you can't see inefficiencies in real time. Empty miles, dwell-time waste, and unoptimised routes compound into millions in avoidable spend.

What we deliver

Our Logistics BI Services

From supply chain BI strategy through to production-grade dashboards and transport analytics consulting, we cover the full stack.

Route Optimisation & Driver Scheduling

VRP solver integration (Google OR-Tools, custom heuristics)
EU Regulation 561/2006 driving-hours compliance built in
Real-time re-routing via live traffic and weather feeds
Multi-depot, time-window, and capacity constraint handling

Supply Chain Visibility Dashboards

End-to-end order tracking from purchase order to proof of delivery
Carrier performance scorecards and lane-level benchmarking
Dwell time analytics to surface port and warehouse bottlenecks
Automated exception alerts pushed to ops teams in real time

Inventory Intelligence

Dynamic safety-stock models driven by demand volatility signals
Supplier risk scoring using lead-time and reliability data
Probabilistic demand forecasting (ML + statistical ensembles)
ABC/XYZ segmentation with reorder-point automation

Last-Mile Delivery Analytics

On-time-in-full (OTIF) rate tracking by depot, carrier, and postcode
NPS correlation analysis to link delivery experience to retention
Failed-delivery root-cause dashboards with driver-level drill-down
Depot efficiency benchmarks: picks per hour, utilisation, throughput

Illustrative scenarios

Use Cases

Illustrative logistics workflows with sample scenarios and figures, not verified customer outcomes.

Illustrative example. These scenarios and sample figures illustrate an approach. They are not verified client results or a promise of savings. Actual scope and outcomes depend on the data, systems and operating conditions.

Spanish Trucking Fleet

340 HGVs across the Iberian Peninsula

Challenge

Fragmented routing across 12 depots, manual tachograph reconciliation, and no unified view of fuel consumption by route or driver.

Solution

Deployed a VRP-based route optimisation engine integrated with their existing TMS, combined with a real-time Power BI dashboard for fleet controllers.

18% reduction in fuel costs within 6 months
94% on-time delivery rate (up from 81%)
EU 561/2006 compliance automated end-to-end
€1.2M annualised saving in fuel and overtime

UK Last-Mile Delivery

Regional parcel carrier, 120 drivers

Challenge

Rising failed-delivery rates, driver overtime spiralling out of control, and no visibility into which depots or routes were underperforming.

Solution

Built a last-mile analytics platform ingesting scan events, driver-app telemetry, and customer NPS data into a unified Snowflake warehouse with dbt transformations.

30% reduction in average delivery time
£1.8M driver overtime savings in year one
Failed delivery rate cut from 8.4% to 2.1%
NPS improved by 22 points within 9 months

Global Retail Inventory

Multi-region retailer, 14 distribution centres

Challenge

Excess inventory in some DCs alongside stockouts in others, no unified demand signal, and a planning process that relied on spreadsheets and gut feel.

Solution

Unified 14 DC inventory systems into a central dbt + Snowflake pipeline, layering an ML demand-forecasting model and dynamic safety-stock calculator on top.

40% fewer stockouts in peak season
15% reduction in overall holding costs
Planner time on replenishment cut by 60%
Supplier lead-time visibility across 800+ SKUs

Our stack

Tools We Use

Purpose-built technologies for logistics analytics — from streaming pipelines and geospatial optimisation through to interactive delivery maps.

Google OR-ToolsApache KafkaPostGISdbt + SnowflakePythonPower BIReact + Mapbox GL JSHERE Maps API

Example measures

Illustrative planning figures

Sample figures illustrate what a measurement plan could compare. No customer baseline or measured result is claimed.

18%

Sample fuel cost reduction

Illustrative scenario: route optimisation and driver scheduling for a multi-depot operation.

40%

Sample reduction in stockouts

Illustrative scenario: safety-stock modelling and demand forecasting for a distribution network.

30%

Sample delivery time improvement

Illustrative scenario: last-mile analytics, exception review and carrier performance reporting.

Illustrative example

Explore how an operational project could work.

These scenarios and sample figures illustrate an approach. They are not verified client results or a promise of savings. Actual scope and outcomes depend on the data, systems and operating conditions.

Urban distribution team coordinating delivery vans

Illustrative example

Last-Mile Logistics

Live routing and warehouse slotting adapted daily plans as demand and traffic changed.

30% faster deliveries

Long-haul trucks moving through a motorway interchange

Illustrative example

Long-Haul Route Optimisation

Driver constraints, traffic, and vehicle capacity became one continuously optimised plan.

18% lower fuel cost

Illustrative example

Inventory Resilience

Supplier-risk signals and dynamic safety stock reduced shortages without excess inventory.

40% fewer stockouts

Ready to build supply chain visibility?

Whether you need route optimisation analytics, a real-time tracking dashboard, or end-to-end supply chain BI, we scope, build, and deliver — in weeks, not months.

Start a conversation

Plan a practical first step

Bring to the assessment

Order, shipment and stop identifiers, planned/actual timestamps, carrier records and one service-level decision.

Define the deliverables

A joined shipment model, defined on-time/dwell measures and an exception dashboard with assigned actions.

Agree how it will run

Resolve missing scans and timezone differences, agree KPI denominators, validate a sample with dispatch and then plan refresh and ownership.

We confirm the demonstrable workflow, data access, integration work and success measures during scoping. Examples illustrate an approach; they are not verified customer results.

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